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220822 ||| eng |
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|a 9783036542287
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|a 9783036542270
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|a books978-3-0365-4228-7
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1 |
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|a Symeonakis, Elias
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|a Land Degradation Assessment with Earth Observation
|h Elektronische Ressource
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260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2022
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300 |
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|a 1 electronic resource (368 p.)
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653 |
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|a South Africa
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653 |
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|a machine learning
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653 |
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|a GEE
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653 |
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|a Landsat
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653 |
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|a land cover
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653 |
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|a drivers
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653 |
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|a unmanned aerial vehicle
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653 |
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|a vegetation index
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653 |
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|a gully mapping
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653 |
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|a breakpoints and timeseries analysis
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653 |
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|a mining development
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653 |
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|a drought
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653 |
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|a central Asia
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653 |
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|a arid and semi-arid areas
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653 |
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|a SDG
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|a greenhouse gas emissions
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653 |
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|a ecosystem structural change
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653 |
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|a sustainable land management programmes
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653 |
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|a drought index
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653 |
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|a precipitation
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653 |
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|a Niger River basin
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653 |
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|a salinity index
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653 |
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|a vegetation-precipitation relationship
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653 |
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|a spatial distribution
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653 |
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|a Sentinel-2 images
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653 |
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|a Earth observation
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|a Research & information: general / bicssc
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|a land productivity
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653 |
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|a slangbos
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653 |
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|a Google Earth Engine
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653 |
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|a archetypes
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653 |
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|a AVHRR
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653 |
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|a Normalised Difference Vegetation Index (NDVI)
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653 |
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|a land surface phenology
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653 |
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|a Amu Darya delta (ADD)
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653 |
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|a drought impacts
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653 |
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|a land use-land cover
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653 |
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|a Vegetation Condition Index (VCI)
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653 |
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|a Kenya
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653 |
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|a trend analysis
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653 |
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|a savannah
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653 |
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|a Kobresia pygmaea community
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653 |
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|a MODIS
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653 |
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|a greening
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653 |
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|a geographically weighted regression (GWR)
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653 |
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|a NDVI
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653 |
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|a Mann-Kendall
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653 |
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|a drought adaptation
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653 |
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|a Sentinel-2
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653 |
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|a shrub encroachment
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653 |
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|a salinized land degradation index (SDI)
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653 |
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|a random forest
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653 |
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|a support vector machines
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653 |
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|a land degradation
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|a vegetation trends
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|a n/a
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|a bfast
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|a Nigeria
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653 |
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|a semi-arid areas
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|a reference levels
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653 |
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|a Gaofen satellite
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|a monitoring and reporting
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653 |
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|a spatial heterogeneity
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653 |
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|a soil organic carbon
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653 |
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|a time series
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653 |
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|a vegetation resilience
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653 |
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|a irrigated systems
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653 |
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|a Soil Adjusted Vegetation Index (SAVI)
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653 |
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|a BFAST
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653 |
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|a self-organizing maps
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653 |
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|a TI-NDVI
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653 |
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|a satellite-based aridity index
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653 |
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|a browning
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653 |
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|a RWEQ
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653 |
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|a spatial-temporal variation
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653 |
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|a satellite imagery
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653 |
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|a East Africa
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653 |
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|a Synthetic Aperture Radar (SAR)
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653 |
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|a remote sensing index
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653 |
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|a land degradation neutrality
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653 |
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|a aridity index
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653 |
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|a Xishuangbanna
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653 |
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|a Uganda
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653 |
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|a drought vulnerability
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653 |
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|a wind erosion modeling
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653 |
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|a standardized precipitation evapotranspiration index
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653 |
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|a REDD+
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653 |
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|a Landsat time series analysis
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653 |
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|a remote sensing
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653 |
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|a pastures
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653 |
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|a Sentinel-1
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|a salinization
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|a semi-arid environment
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653 |
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|a high temporal resolution
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653 |
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|a Sen's slope
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653 |
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|a Kyrgyzstan
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653 |
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|a breakpoint analysis
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653 |
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|a land use
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653 |
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|a Botswana
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653 |
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|a developing countries
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700 |
1 |
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|a Symeonakis, Elias
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041 |
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7 |
|a eng
|2 ISO 639-2
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|b DOAB
|a Directory of Open Access Books
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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8 |
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|a 10.3390/books978-3-0365-4228-7
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856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/84553
|z DOAB: description of the publication
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4 |
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|u https://www.mdpi.com/books/pdfview/book/5537
|7 0
|x Verlag
|3 Volltext
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|a 363
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|a 000
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|a 333
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|a 700
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|a This Special Issue (SI) on "Land Degradation Assessment with Earth Observation" comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps-some of which have been identified in this SI-and produce highly accurate and relevant land-degradation assessment and monitoring tools.
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